GEO: The Only AI Search Term That Matters

For 20+ years, search was simple: type a query into Google, get a ranked list of links, click, and explore. Visibility meant one thing—ranking high. But that model is quickly fading.

AI-powered platforms like ChatGPT, Perplexity, and Claude are rewriting the rules. Instead of serving up links, they deliver full-text responses. Users no longer need to click through to a webpage because the answer is already there.

As this shift takes hold, new terminology has emerged to describe how we optimize for these systems: Answer Engine Optimization (AEO), AI Optimization (AIO), Generative Engine Optimization (GEO), and Large Language Model Optimization (LLMO).

Despite the different names, they all describe the same goal: improving how your brand is surfaced and represented in AI-generated responses. In this post, we’ll break down what these terms mean and why we’re choosing the term “GEO” as the umbrella term for AI-driven search. 

Search engine & search engine optimization (SEO)

A search engine (think traditional Google or Bing experience) indexes and ranks web pages based on relevance, links, and on-page signals. It doesn’t create content—it filters and organizes existing content. The user journey is straightforward:

Type a query → Get a list of ranked links “10 blue links”→ Click on a result → Land on a website →Explore multiple sources → Piece together an answer.

Search engine optimization (SEO) refers to the strategies and tactics to ensure your brand ranks effectively on search engine results pages (SERPs). These strategies include keyword research, on-page optimizations, technical SEO, and link building, among others. The goal? Drive traffic by being discoverable. 

Generative engines, answer engines, AI Overviews, and large language models

Enter the new generation of search: generative engines, answer engines, and AI Overviews. These aren’t just new interfaces—they’re fundamentally different systems.

These systems don’t retrieve answers, they create them using large datasets and LLMs to generate new, conversational responses. (Note: AI Overviews are a branded term for Google’s AI-driven search experience.) 

Unlike traditional search engines, which present a list of websites for searchers to click through and piece together answers, AI-driven search experiences deliver direct answers in a conversational format. The user journey looks something like this:

Ask a question → Receive a synthesized AI-generated answer →Refine the query → AI adapts to provide deeper, more tailored responses → Continue engaging in dialogue to retrieve answers.

GEO, AEO, AIO, LLMO

Generative engine optimization (GEO), answer engine optimization (AEO), AI optimization (AIO), and large language model optimization (LLMO) are terms used to describe strategies and tactics to improve a brand’s visibility within AI-driven search experiences.

While traditional SEO focuses on ranking content in SERPs, GEO, AEO, AIO, and LLMO are about shaping how LLMs present your brand and content. This new search paradigm presents several new dynamics:

1. Rather than presenting information verbatim from your content (e.g., Google Snippets), AI models may summarize your content with or without a citation. This means metrics like “click through rate” CTR are no longer a solid, standalone performance metric.

2. When your brand is cited, an AI-generated response may combine multiple sources. This means your brand could be featured at the beginning of the response or further down, which could dilute your visibility. Simply tracking presence within AI-generated responses is not enough. 

3. There is no single framework for how LLM platforms generate responses. Not to mention, LLMs are changing in real time to compete with a growing set of AI platforms. This means teams must tailor their strategies to different platforms (i.e., showing up in ChatGPT might require a different strategy than showing up in Perplexity).

Bringing it all together: GEO

At daydream, we’ve adopted GEO as the umbrella term for optimizing AI-driven search. Here’s why:

1. GEO is universal. While terms like “large language models” (LLMs) and “answer engines” typically refer to text-based applications, the word generative encompasses a wider range of media. That includes generating text, images, audio, video, and other formats. As search evolves, AI will shape how all types of content are created and discovered.

2. The other terms are subsets of GEO. LLMs are the foundational models that power text-based generative engines. Answer engines like Perplexity build on top of LLMs and focus on specific tasks, such as responding to queries or summarizing information. GEO, by contrast, covers the full strategy required to optimize for all types of AI-generated content across different platforms and use cases.

GEO is the new SEO. As AI-driven platforms take over more search queries, search is no longer just about where you rank; it’s about how AI interprets, summarizes, and presents your brand. To stay ahead, you need a strategy that optimizes for both traditional SEO and AI-driven discovery, ensuring your content isn’t just visible but influential in AI-generated experiences.

At daydream, we help companies build resilient, AI-ready growth engines. Our full-service approach ensures you stay competitive in traditional search while proactively shaping your presence in AI-powered search experiences. If you’re ready to future-proof your strategy, let’s talk.